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Chapter 5: Problem 39

To study the effectiveness of vitamin \(C\) in preventing colds, a researcher recruited 200 volunteers. She randomly assigned 100 of them to take vitamin \(C\) for 10 weeks and the remaining 100 to take nothing. The 200 participants recorded how many colds they had during the 10 weeks. The two groups were compared, and the researcher announced that taking vitamin C reduces the frequency of colds.

Short Answer

Expert verified
Vitamin C appears to reduce the frequency of colds based on fewer colds reported by the treatment group compared to the control group.

Step by step solution

01

Identify the Experimental Groups

The researcher divides the participants into two groups: one group takes vitamin C (treatment group), and the other group takes nothing (control group). Each group consists of 100 participants.
02

Duration of the Study

Each participant in both groups records the number of colds they experience over a duration of 10 weeks.
03

Data Collection

The researcher collects data by counting the number of colds reported by each participant in both groups over the study period.
04

Data Comparison

The researcher compares the average number of colds in the vitamin C group to the average number in the control group to see if there is a difference.
05

Conclusion

Based on this comparison, if the vitamin C group has fewer colds on average than the control group, the researcher concludes that vitamin C reduces the frequency of colds.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Control Group
In any experimental study, the control group plays a vital role. It acts as a baseline that researchers compare against. In our vitamin C study, the control group consists of 100 participants who did not take any vitamin C. They simply went about their normal daily routine.

By not administering the treatment (vitamin C) to this group, researchers can determine whether any observed effects are due to the treatment itself or other factors. This group essentially shows what happens without the intervention, providing a clear benchmark to gauge the impact of the treatment group.
Treatment Group
The treatment group is the set of participants who receive the experimental treatment鈥攊n this case, vitamin C. This group also includes 100 participants who took vitamin C over the 10-week study period.

By giving the treatment to this group, researchers observe its potential effects. This setup allows them to measure the differences in outcomes鈥攕uch as the number of colds experienced鈥攂etween this group and the control group.
  • The treatment is crucial for answering the research question.
  • It helps test the hypothesis about vitamin C鈥檚 effectiveness against colds.
Data Collection
Data collection is a crucial phase of any experimental research. In this vitamin C study, it involves gathering information on how many colds each participant has over ten weeks.

Participants actively record their experiences during the study, creating a set of data points for analysis.
  • Ensures the accuracy of the research findings.
  • Helps identify any trends or patterns in the data.
Accurate data collection is fundamental to provide reliable evidence to support or refute the research hypothesis.
Data Comparison
Once data is collected, comparing it between the groups is key to understanding the effects of the treatment. In this study, researchers look at the average number of colds in both the treatment and control groups.

By evaluating these averages, they can determine if there's a significant difference between taking vitamin C and not taking any supplement.
  • Data comparison illuminates whether the treatment yields beneficial outcomes.
  • Helps assess the validity of the hypothesis that vitamin C can reduce cold frequency.
This comparison is what allows for drawing meaningful conclusions about the efficacy of the intervention.

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Most popular questions from this chapter

Is it possible to conduct a randomized experiment to compare two conditions using volunteers recruited through a local newspaper? If not, explain why not. If so, explain how it would be done and explain any "difficulties and disasters" that would be encountered.

Suppose researchers were interested in determining the relationship. if any, between brain cancer and the use of cell phones. Would it be better to use a randomized experiment or a case-control study? Explain.

Researchers have found that women who take oral contraceptives (birth control pills) are at higher risk of having a heart attack or stroke than women who do not take them. They also found that the risk is substantially higher for both groups if a woman smokes. Assume that the proportions of women who smoke are similar in both groups. In investigating the relationship between taking oral contraceptives (the explanatory variable) and having a heart attack or stroke (the response variable), explain whether smoking would fit the definition of each of the following: a. A confounding variable. b. An effect modifier. c. An interacting variable.

Is the "experimenter effect" most likely to be present in a double-blind experiment, a single-blind experiment, or an experiment with no blinding? Explain.

To compare four brands of tires, one of each brand was randomly assigned to the four tire locations on each of 50 cars. These tires were specially manufactured without any labels identifying the brand. After the tires had been on the cars for 30.000 miles, the researchers removed them and measured the remaining tread. They were not told which brand was which until the experiment was over. a. What was the explanatory variable in this experiment? b. What was the response variable in this experiment? c. Was this experiment single-blind, double-blind, or neither? Explain. d. Did this experiment use matched pairs, blocks, or neither? Explain.
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